Design and analysis of optimal material distribution policies in flexible manufacturing systems using a single automated guided vehicle

Modern automated manufacturing processes employ Automated Guided Vehicles (AGVs) for material handling, which serve several machine centres (MCs) in a factory. Waiting times for resources such as AGVs are the longest elements that make up the Manufacturing Lead Time (MLT). Hence, optimal scheduling of AGVs can significanlty help to increase the efficiency of the manufacturing process by minimizing the idle time of MCs waiting for the raw materials. In this paper, we will analyse the requirements for an optimal schedule and then provide a mathematical framework for an efficient schedule of material delivery by an AGV. The optimal schedule depends on several factors, such as the processing speeds of MCs, the speed and the material carrying capacity of the AGV, and system dependent overheads (such as loading and unloading time, machine set-up time, distance travelled, etc). A mathematical model is developed and then a strategy for optimal material distribution of the available raw material to the MCs is derived. With this model, the optimal number of MCs to be utilized will also be determined. Finally, the material delivery schedule employing multiple journeys to the MCs by the AGV will be carried out. Through rigorous analysis and simulation experiments, we shall show that such a delivery strategy will optimize the overall performance.